Measuring real world sizes in photographs is emerging as a valuable and important capability in portable devices such as smartphones, tablets, and cameras. Size measurements may be used for entertainment and recreational purposes e.g. how big is that fish I caught, to utilitarian purposes, e.g. how much paint will this wall require, or will that couch fit in my house. The affordability of accurate small cameras has driven great interest and experimentation with uses for multiple camera arrays especially for 3D (three dimensional) capabilities.
When there are two or more cameras on a device, the distance from the cameras to an object in the captured scene is referred to as depth. Typically depth is stored as image metadata for each pixel of an image. Each pixel therefore corresponds to an object that is some distance from the camera. Depth photography systems generate depth maps using disparity information from different images of the same scene taken by different cameras on the device. Depth-enhanced photography enables a wide range of interactive, user interface (UX) applications including estimate-driven measurement and sizing applications in non-precision, consumer use cases.
The depth of an object i.e. its distance from the cameras is measured using a discrete pixel disparity. By comparing the position in image pixels of the object in different images of the scene. Disparity works better for closer items because the disparity is greater. The error in depth determinations grows exponentially with distance from the camera. Disparity maps are also limited by the noise in the two images that are compared.